Denoising Architecture for Unsupervised Anomaly Detection in Time-Series
Conference Proceeding
Skaf, W., & Horváth, T. (2022)
Denoising Architecture for Unsupervised Anomaly Detection in Time-Series. In S. Chiusano, T. Cerquitelli, R. Wrembel, K. Nørvåg, B. Catania, G. Vargas-Solar, & E. Zumpano (Eds.), New Trends in Database and Information Systems: ADBIS 2022 Short Papers, Doctoral Consortium and Workshops: DOING, K-GALS, MADEISD, MegaData, SWODCH, Turin, Italy, September 5–8, 2022, Proceedings (178-187). https://doi.org/10.1007/978-3-031-15743-1_17
Anomalies in time-series provide insights of critical scenarios across a range of industries, from banking and aerospace to information technology, security, and medicine. How...
Directed Undersampling Using Active Learning for Particle Identification
Conference Proceeding
Farou, Z., Ouaari, S., Domian, B., & Horváth, T. (2022)
Directed Undersampling Using Active Learning for Particle Identification. In P. Kumar Singh, Y. Singh, J. Kumar Chhabra, Z. Illés, & C. Verma (Eds.), Recent Innovations in Computing: Proceedings of ICRIC 2021, Volume 2 (149-162). https://doi.org/10.1007/978-981-16-8892-8_12
Tracing the Local Breeds in an Outdoor System – A Hungarian Example with Mangalica Pig Breed
Book Chapter
Alexy, M., & Horváth, T. Tracing the Local Breeds in an Outdoor System – A Hungarian Example with Mangalica Pig Breed. In Tracing the Domestic Pig. IntechOpen. https://doi.org/10.5772/intechopen.101615)
Alexy, M., & Horváth, T. Tracing the Local Breeds in an Outdoor System – A Hungarian Example with Mangalica Pig Breed. In Tracing the Domestic Pig. IntechOpen. https://doi.org/10.5772/intechopen.101615
Pig farming is largely characterized by closed, large-scale housing technology. These systems are driven by resource efficiency. In intensive technologies, humans control almo...
Migrating Models: A Decentralized View on Federated Learning
Conference Proceeding
Kiss, P., & Horváth, T. (2021)
Migrating Models: A Decentralized View on Federated Learning. In Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I (177-191). https://doi.org/10.1007/978-3-030-93736-2_15
Federated learning (FL) researches attempt to alleviate the increasing difficulty of training machine learning models, when the training data is generated in a massively distr...
Time-Series in Hyper-parameter Initialization of Machine Learning Techniques
Conference Proceeding
Horváth, T., Mantovani, R. G., & de Carvalho, A. C. P. L. F. (2021)
Time-Series in Hyper-parameter Initialization of Machine Learning Techniques. In Intelligent Data Engineering and Automated Learning – IDEAL 2021: 22nd International Conference, IDEAL 2021, Manchester, UK, November 25–27, 2021, Proceedings (246-258). https://doi.org/10.1007/978-3-030-91608-4_25
Initializing the hyper-parameters (HPs) of machine learning (ML) techniques became an important step in the area of automated ML (AutoML). The main premise in HP initializatio...
Linear Concept Approximation for Multilingual Document Recommendation
Book Chapter
Salamon, V. T., Tashu, T. M., & Horváth, T. (2021)
Linear Concept Approximation for Multilingual Document Recommendation. . Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-030-91608-4_15
In this paper, we proposed Linear Concept Approximation, a novel multilingual document representation approach for the task of multilingual document representation and recomme...
Multimodal Emotion Recognition from Art Using Sequential Co-Attention
Journal Article
Tashu, T. M., Hajiyeva, S., & Horvath, T. (2021)
Multimodal Emotion Recognition from Art Using Sequential Co-Attention. Journal of Imaging, 7(8), Article 157. https://doi.org/10.3390/jimaging7080157
In this study, we present a multimodal emotion recognition architecture that uses both feature-level attention (sequential co-attention) and modality attention (weighted modal...
Attention-Based Multi-modal Emotion Recognition from Art
Conference Proceeding
Tashu, T. M., & Horváth, T. (2021)
Attention-Based Multi-modal Emotion Recognition from Art. In Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings, Part III (604-612). https://doi.org/10.1007/978-3-030-68796-0_43
Emotions are very important in dealing with human decisions, interactions, and cognitive processes. Art is an imaginative human creation that should be appreciated, thought-pr...
A Novel Evaluation Metric for Synthetic Data Generation
Conference Proceeding
Galloni, A., Lendák, I., & Horváth, T. (2020)
A Novel Evaluation Metric for Synthetic Data Generation. In Intelligent Data Engineering and Automated Learning – IDEAL 2020: 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II (25-34). https://doi.org/10.1007/978-3-030-62365-4_3
Differentially private algorithmic synthetic data generation (SDG) solutions take input datasets Dp consisting of sensitive, private data and generate synthetic data Ds with s...
Data Generation Using Gene Expression Generator
Conference Proceeding
Generative adversarial networks (GANs) could be used efficiently for image and video generation when labeled training data is available in bulk. In general, building a good ma...